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CSFwinformer: Cross-Space-Frequency Window Transformer for Mirror Detection

This repo is the official implementation of CSFwinformer: Cross-Space-Frequency Window Transformer for Mirror Detection (IEEE TIP 2024).

Installation

conda create -n md python=3.7 -y
conda activate md

conda install pytorch==1.7.1 torchvision==0.8.2 torchaudio==0.7.2 cudatoolkit=11.0 -c pytorch
pip install mmcv-full==1.4.0 -f https://download.openmmlab.com/mmcv/dist/cu110/torch1.7.1/index.html

cd CSFwinformer

pip install -e .
pip install -r requirements/optional.txt

mkdir data

Data Preparation

"MSD"

"PMD"

"RGBD-Mirror"

You can download zip files for corresponding three datasets from "here"

Train

python tools/train.py configs/mirror/pmd_mirror_swin_small.py

Test

python ./tools/test.py configs/mirror/pmd_mirror_swin_small.py work_dirs/pmd_mirror_swin_small/your_weight --show-dir ./results/pmd --eval mIoU

Results and Models

Dataset Backbone IoU↑ Acc↑ $F_β$ MAE↓ BER↓
PMD swin_s 69.84 77.28 0.849 0.024 11.91
PMD swin_b 70.05 78.27 0.838 0.024 11.41
MSD swin_s 82.13 88.72 0.895 0.046 7.15
MSD swin_b 82.08 88.92 0.896 0.045 7.14
RGBD-Mirror swin_b 78.66 84.64 0.900 0.031 8.57

You can find all weights from "here"

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